The ever-growing field of mathematical biosciences

In the last two years, the College of Science has focused on augmenting its expertise in data and life sciences with strategic hires in mathematical biology and bioinformatics. Almost immediately the new faculty have strengthened interdisciplinary and collaborative research in the College as well as across OSU.

These faculty have quickly connected with scientists across campus, paving the way for interdisciplinary research and broader training of graduate and undergraduate students in different areas of science.

David Hendrix

Duo Jiang

David Koslicki

Patrick De Leenheer

Thomas Sharpton

Among the key hires are David Hendrix, assistant professor of biochemistry/biophysics and computer science; Duo Jiang, assistant professor of statistics; David Koslicki, assistant professor of mathematics; Patrick De Leenheer, professor of mathematics and integrative biology; Thomas Sharpton, assistant professor of microbiology and statistics.

“I am thrilled to welcome this extraordinarily talented cohort to the College,” said Sastry G. Pantula, dean of the College of Science.

“They will strengthen our foundation in fundamental sciences while building bridges to enable discoveries in other sciences, engineering and education.”

While the need for mathematical biosciences has grown rapidly due to massive sets of data in life sciences, computational and mathematical algorithms and new statistical methodology, the current community of mathematical bioscientists remains relatively small. The new faculty will strengthen the College’s efforts to advance research at the intersection of mathematical, statistical and biosciences research and nurture a new generation of scientists in a comprehensive, systematic way.

Mathematical Biology: What is it?

De Leenheer is one of a growing number of researchers worldwide who works in both the mathematical and biological sciences. De Leenheer uses mathematics to better understand how a variety of biological systems behave.

Although mathematical biology evolved throughout the twentieth-century, only in the last couple decades has it become its own branch of applied mathematics, primarily because research in biology and medicine has become more dependent on mathematics and computation. To illustrate, federal agencies such as NSF have initiated programs in Mathematical Biology and Research at the Interface of Biological, Mathematical and Physical Sciences.

De Leenheer uses dynamical mathematical models that describe and illuminate biological processes ranging from the cellular to the ecological scale. Currently, he is developing new modeling approaches for the analysis and design of Marine Protected Areas (MPA) to enhance fisheries as part of an NSF-funded project. This work will be instrumental in better informing policymakers on MPA implementation.

Bioinformatics: The new age of data

Bioinformatics professors David Koslicki and Thomas Sharpton have found Oregon State particularly favorable for their research, thanks to the extremely collaborative culture and the high-quality biological and computing resources at the Center for Genome Research and Biocomputing.

“A transdisciplinary field, bioinformatics requires expertise in biology, computer science, mathematics and statistics. It’s rare that one researcher has sufficient expertise in all these areas so collaboration is often needed to solve a problem,” says Sharpton.

“OSU is easily the most collaborative environment that I have been a part of, and the supportive and interactive nature of my colleagues helps produce more impactful bioinformatic discoveries at a faster rate.”

Bioinformatics, which is the creation of software tools, algorithms and databases to analyze biological data, evolved into a discipline in the 1970s with the development of DNA sequencing. The explosive quantities of genomics-related data have spurred the growth of bioinformatics databases and tools for a variety of biological fields: medicine, microbiology, ecology, pharmacology, and many more.

“We have massive data sets that have the ability to transform many different fields,” says Koslicki. “But you need algorithms that are extremely efficient to be able to analyze these things.”

So, what does a bioinformatics project look like?

Koslicki invented a bacterial community reconstruction tool in which he sequenced the DNA of an environmental sample to determine which bacteria were present. Using an optimization technique derived from mathematical theory, Koslicki developed a swifter, more accurate method of classifying bacteria.

“Simultaneously, we were able to develop the algorithm to help the biology as well as learn some new mathematics about these compressed sensing techniques that hadn’t been observed before,” remarked Koslicki.

Spanning microbiology and statistics, Sharpton’s lab researches DNA sequences of microorganisms that live on the human body, known as the human microbiome, to understand how they influence health.

“Bioinformatics is critical to our work,” says Sharpton.

“We develop and apply computational and statistical methods to ascertain which microbes comprise the human microbiome, their biological functions, and their association with human health.”

The College of Science is investing in young, diverse faculty whether it’s to advance OSU’s Marine Studies Initiative or national priorities like precision medicine. Currently we are recruiting a quantitative biologist, two computational biologists and senior leaders in mathematics and statistics.

Teaching the next generation of students

Mathematical biology has a reputation for being one of the most difficult branches of applied mathematics, but that only spurs Leenheer and Koslicki’s determination to mentor and train the next generation of students who will work at the intersection of mathematics and biology.

“The important thing as I train graduate students is that they should have a solid mathematical background,” says Koslicki. “Presently, I am teaching the probability sequence. Probability is key for the kinds of things I do. In addition, students need to be able to program and to work with these big data kind of problems.”

De Leenheer adds, “In the next five years, I hope to see biology students who have taken certain math courses in order to go to that next step and start using math as a tool in their own research. That would be fantastic.”